The Department of Energy (DOE)-National Cancer Institute (NCI) Collaboration was formed to jointly accelerate federal missions in precision oncology and computing through an alignment of needs and has been driven by three key national initiatives: the National Strategic Computing Initiative, the Precision Medicine Initiative, and the Beau Biden Cancer Moonshot. NCI has a critical need for increased computational capacity and sophisticated computational models to identify promising new treatments; deepen understanding of cancer biology; understand the impact of new diagnostics, treatments, and patient factors in cancer outcomes at the individual patient level; and to integrate pre-clinical model data for cancer research, diagnosis and treatment. DOE has a need for partnerships with user communities to broaden the functionality of next-generation high-performance computers and to advance the DOE mission in low dose radiation and systems biology for energy applications. The DOE-NCI Collaboration brings together the High Performance Computing (HPC) expertise and resources of the DOE with the NCI cancer biology and oncology knowledge base, infrastructure and data repositories to support accelerating capable exascale computing technologies and advance the frontiers of precision oncology, computational and data science, and advanced computing applied to cancer. Initial collaborations between the NCI and DOE were fueled by the National Strategic Computing Initiative (NSCI) 2015 executive order, which promotes a whole-of-government approach to bringing the unique national computing capabilities of lead agencies to transform broad deployment agency missions while meeting their own mission objectives. The DOE, a lead agency for NSCI, partnered with NCI, a broad deployment agency for NSCI, to develop exascale ready tools, algorithms, and capabilities to enhance precision medicine for cancer; this further aligns the DOE-NCI Collaboration initiated under NSCI with the Precision Medicine Initiative and the Beau Biden Cancer Moonshot. Collaborative projects already underway between the DOE-NCI include the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) pilot projects, Exascale CANcer Distributed Learning Environment (CANDLE), and the Accelerating Therapeutics for Opportunities in Medicine (ATOM) Consortium, a public-private partnership under the Cancer Moonshot aimed at changing drug discovery and design paradigms through the application of computational/in silico technologies. The challenges within each JDACS4C pilot were used to shape the priorities for CANDLE, a DOE-supported Exascale Computing Project involving multiple HPC vendors, which addresses a shared need across the pilots to develop predictive models using large-scale data. Exploiting exascale technologies and capabilities anticipated for deep and machine learning, CANDLE will deliver an open source, collaboratively developed software platform providing deep learning methodologies to the community that will be used to advance precision oncology. In addition, it will establish a new paradigm for cancer research for years to come by making effective use of the ever-growing volumes and diversity of cancer-related data to build predictive models, provide better understanding of the biology underlying disease and, ultimately, provide guidance and support decisions on anticipated outcomes of treatment for individual patients.